diff options
Diffstat (limited to 'tests/validation/reference/ConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/reference/ConvolutionLayer.cpp | 190 |
1 files changed, 6 insertions, 184 deletions
diff --git a/tests/validation/reference/ConvolutionLayer.cpp b/tests/validation/reference/ConvolutionLayer.cpp index b7ed2f56c0..24bbf32a30 100644 --- a/tests/validation/reference/ConvolutionLayer.cpp +++ b/tests/validation/reference/ConvolutionLayer.cpp @@ -25,6 +25,7 @@ #include "tests/validation/FixedPoint.h" #include "tests/validation/Helpers.h" +#include "tests/validation/reference/Convolution3d.h" #include "tests/validation/reference/Utils.h" #include "tests/validation/reference/UtilsQuantizedAsymm.h" @@ -42,185 +43,6 @@ namespace reference { namespace { -inline bool is_valid_pixel(int i, int min, int max) -{ - return (i >= min && i < max); -} - -// 3D convolution for floating point type -template < typename T, typename TB, typename std::enable_if < is_floating_point<T>::value &&is_floating_point<TB>::value, int >::type = 0 > -void convolution3d(const SimpleTensor<T> &in, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, SimpleTensor<T> &out, - int i_offset, int w_offset, int b_offset, int o_offset, - int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights) -{ - const T *in_ptr = in.data() + i_offset; - const T *w_ptr = weights.data() + w_offset; - const TB *b_ptr = bias.data() + b_offset; - T *out_ptr = out.data() + o_offset; - - const int half_width_weights_start = width_weights / 2; - const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; - const int half_height_weights_start = height_weights / 2; - const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; - - // Reset accumulator - T acc(0); - - // Compute a 2D convolution for each IFM and accumulate the result - for(int ifm = 0; ifm < depth_in; ++ifm) - { - // Compute the offset for the input slice - const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; - - // Compute 2D convolution - for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) - { - for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) - { - // Check if the pixel is out-of-bound - if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) - { - const int idx = xk + half_width_weights_start; - const int idy = yk + half_height_weights_start; - - const T i_value = in_ptr[offset_slice_in + xk + yk * width_in]; - const T w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights]; - - acc += i_value * w_value; - } - } - } - } - - // Accumulate the bias and store the result - *out_ptr = acc + (*b_ptr); -} - -// 3D convolution for fixed point type -template < typename T, typename TB, typename std::enable_if < std::is_integral<T>::value &&std::is_integral<TB>::value, int >::type = 0 > -void convolution3d(const SimpleTensor<T> &in, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, SimpleTensor<T> &out, - int i_offset, int w_offset, int b_offset, int o_offset, - int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights) -{ - const T *in_ptr = in.data() + i_offset; - const T *w_ptr = weights.data() + w_offset; - const T *b_ptr = bias.data() + b_offset; - T *out_ptr = out.data() + o_offset; - int fixed_point_position = in.fixed_point_position(); - - const int half_width_weights_start = width_weights / 2; - const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; - const int half_height_weights_start = height_weights / 2; - const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; - - using namespace fixed_point_arithmetic; - using promoted_type = fixed_point_arithmetic::traits::promote_t<T>; - - // Reset accumulator - fixed_point<promoted_type> acc(0, fixed_point_position); - - // Compute a 2D convolution for each IFM and accumulate the result - for(int ifm = 0; ifm < depth_in; ++ifm) - { - // Compute the offset for the input slice - const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; - - // Compute 2D convolution - for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) - { - for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) - { - // Check if the pixel is out-of-bound - if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) - { - const int idx = xk + half_width_weights_start; - const int idy = yk + half_height_weights_start; - - const fixed_point<promoted_type> i_value(in_ptr[offset_slice_in + xk + yk * width_in], fixed_point_position, true); - const fixed_point<promoted_type> w_value(w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights], fixed_point_position, true); - const fixed_point<promoted_type> iw = i_value * w_value; - acc = iw + acc; - } - } - } - } - - // Get the bias - const fixed_point<promoted_type> b(*b_ptr, fixed_point_position, true); - - // Accumulate the bias and covert back - acc = acc + b; - fixed_point<T> res(acc); - *out_ptr = res.raw(); -} - -// 3D convolution for QASYMM8 type -template <> -void convolution3d(const SimpleTensor<uint8_t> &in, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, SimpleTensor<uint8_t> &out, - int i_offset, int w_offset, int b_offset, int o_offset, - int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights) -{ - const uint8_t *in_ptr = in.data() + i_offset; - const uint8_t *w_ptr = weights.data() + w_offset; - const int32_t *b_ptr = bias.data() + b_offset; - uint8_t *out_ptr = out.data() + o_offset; - - const int input_offset = -in.quantization_info().offset; - const float input_scale = in.quantization_info().scale; - const int weights_offset = -weights.quantization_info().offset; - const float weights_scale = weights.quantization_info().scale; - const int output_offset = out.quantization_info().offset; - const float output_scale = out.quantization_info().scale; - - int output_multiplier = 0; - int output_shift = 0; - const float multiplier = input_scale * weights_scale / output_scale; - arm_compute::quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - - const int half_width_weights_start = width_weights / 2; - const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; - const int half_height_weights_start = height_weights / 2; - const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; - - // Reset accumulator - int32_t acc(0); - - // Compute a 2D convolution for each IFM and accumulate the result - for(int ifm = 0; ifm < depth_in; ++ifm) - { - // Compute the offset for the input slice - const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; - - // Compute 2D convolution - for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) - { - for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) - { - // Check if the pixel is out-of-bound - if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) - { - const int idx = xk + half_width_weights_start; - const int idy = yk + half_height_weights_start; - - const uint8_t i_value = in_ptr[offset_slice_in + xk + yk * width_in]; - const uint8_t w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights]; - - acc += (i_value + input_offset) * (w_value + weights_offset); - } - } - } - } - - // Accumulate the bias - acc += (*b_ptr); - - acc = asymm_rounding_divide_by_pow2(asymm_int_mult(acc, output_multiplier), output_shift); - acc += output_offset; - acc = utility::clamp<int32_t>(acc, 0, 255); - - // Store the result - *out_ptr = acc; -} } // namespace template <typename T, typename TB> @@ -270,11 +92,11 @@ SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor ARM_COMPUTE_ASSERT(yo < height_out); // Compute 3D convolution - convolution3d(src, weights, bias, dst, - offset_in, ofm * width_weights * height_weights * depth_weights, ofm, offset_out, - xi, yi, - width_in, height_in, depth_in, - width_weights, height_weights); + convolution_3d::detail::convolution3d(src, weights, bias, dst, + offset_in, ofm * width_weights * height_weights * depth_weights, ofm, offset_out, + xi, yi, + width_in, height_in, depth_in, + width_weights, height_weights); } } } |